RTM Stacking Results for Machine Translation Performance Prediction

Ergun Biçici. RTM Stacking Results for Machine Translation Performance Prediction. In Proc. of the Fourth Conference on Statistical Machine Translation (WMT19), Florence, Italy, August 2019.

We obtain new results using referential translation machines with increased number of learning models in the set of results that are stacked to obtain a better mixture of experts prediction. We combine features extracted from the word-level predictions with the sentence- or document-level features, which significantly improve the results on the training sets but decrease the test set results.